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Titlebook: Dynamical Behaviors of Fractional-Order Complex Dynamical Networks; Jin-Liang Wang Book 2024 The Editor(s) (if applicable) and The Author(

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書(shū)目名稱Dynamical Behaviors of Fractional-Order Complex Dynamical Networks
編輯Jin-Liang Wang
視頻videohttp://file.papertrans.cn/284/283823/283823.mp4
概述Provides a comprehensive overview of the dynamical behaviors for fractional-order complex networks.Illustrates the relationship between the synchronization and passivity for fractional-order complex n
圖書(shū)封面Titlebook: Dynamical Behaviors of Fractional-Order Complex Dynamical Networks;  Jin-Liang Wang Book 2024 The Editor(s) (if applicable) and The Author(
描述.This book benefits researchers, engineers, and graduate students in the field of fractional-order complex dynamical networks. Recently, the dynamical behaviors (e.g., passivity, finite-time passivity, synchronization, and finite-time synchronization, etc.) for fractional-order complex networks (FOCNs) have attracted considerable research attention in a wide range of fields, and a variety of valuable results have been reported. In particular, passivity has been extensively used to address the synchronization of FOCNs.?.
出版日期Book 2024
關(guān)鍵詞Fractional-order; complex dynamical networks; coupled neural networks; multiple derivative couplings; mu
版次1
doihttps://doi.org/10.1007/978-981-97-2950-0
isbn_softcover978-981-97-2952-4
isbn_ebook978-981-97-2950-0
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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,Synchronization and?Adaptive Control for?Coupled Fractional-Order Reaction-Diffusion Neural Networkce fractional-order neural networks (FONNs) can more effectively and accurately describe human brain neurons, plenty of work has been devoted to the dynamical behavior for FONNs [.,.,.,.,.,.]. The stability for fractional-order delayed Hopfield NNs was addressed in [.], and the cases that the networ
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Passivity of Coupled Fractional-Order Neural Networks with Multiple State and Derivative Couplings,have been extensively explored, which is not only beneficial to better understand the dynamical characteristics of the NNs but also to make better use of these dynamical behaviors in many fields such as model identification, parallel computation and combinatorial optimization.
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,Passivity for?Multiadaptive Coupled Fractional-Order Reaction-Diffusion Neural Networks,rently depend on the stability of NNs. Therefore, a large number of stability results for all kinds of NNs have been given in recent years [.,.,.,.,.,.,.,.]. Li et al. [.] introduced a state-dependent switched fuzzy NN including discrete delay and distributed delay, and developed several exponential
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